CiLiQuant: Quantification of RNA Junction Reads Based on Their Circular or Linear Transcript Origin

Area of Science:

• Bioinformatics
• Computational Biology
• Genomics

Background:

• Circular RNAs (circRNAs) are increasingly recognized as important regulatory molecules.
• Differentiating circRNAs from their linear counterparts is crucial for accurate transcriptomic analysis.
• Sequence overlap between linear and circular RNA reads presents a significant computational challenge.

Purpose of the Study:

• To develop a computational method for distinguishing and quantifying circular RNA reads from linear host transcripts.
• To address the challenge of sequence overlap in circRNA detection.
• To provide a tool for assessing the relative abundance of circular and linear RNA species.

Main Methods:

• Development of a computational approach named CiLiQuant.
• Utilizing back-splice junction reads specific to circRNAs.
• Employing unambiguous forward-splice junction reads from linear transcripts.
• Leveraging existing mapping and circRNA discovery tools.

Main Results:

• CiLiQuant accurately determines the relative abundance of circular and linear RNA transcripts.
• The method effectively distinguishes between circular and linear RNA reads based on splice junction information.
• Gene loci abundance for both circular and linear forms can be determined.

Conclusions:

• CiLiQuant offers a robust solution for the accurate quantification of circular and linear RNA.
• The developed computational approach overcomes the challenge of sequence overlap.
• This tool facilitates a more precise understanding of circRNA regulation and function.